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Analytics 50: How big data innovators reap results

Five winners of the 2016 CIO.com and Drexel University Analytics 50 awards share details of their projects, lessons learned and advice.

By Thor Olavsrud as written on cio.com

Data and analytics are reshaping organizations and business processes, giving organizations the capability to interrogate internal and external data to better understand their customers and drive transformative efficiencies.

Worldwide revenues for big data and business analytics clocked in at nearly $122 billion in 2015 and will grow to $187 billion in 2019, according to a five-year forecast from research firm IDC.

“Organizations able to take advantage of the new generation of business analytics solutions can leverage digital transformation to adapt to disruptive changes and create competitive differentiation in their markets,” said IDC analyst Dan Vesset in a statement issued in conjunction with the release of IDC’s Worldwide Semiannual Big Data and Analytics Spending Guide earlier this year. “These organizations don’t just automate existing processes — they treat data as they would any valued asset by using a focused approach to extracting and developing the value of information.”

Additionally, a recent Forrester Research study, commissioned by the global data and analytics team at KPMG, found that 50 percent of businesses now use data and analytics tools to analyze their existing customers, while 48 percent use them to find new customers and 47 percent use them to develop new products and services.

The picture isn’t entirely rosy, however. That same Forrester study found that many organizations are struggling to adjust their cultures to a world in which data and analytics play a central role, and many business executives mistrust the insights generated by data and analytics.

Other organizations, however, have taken naturally to data and analytics and are using new tools to better understand customers, develop new products and optimize business processes.

To honor those organizations, CIO.com and Drexel University’s LeBow College of Business recently announced the first Analytics 50 awards. The winners represent a broad spectrum of industries, from pharmaceuticals and healthcare to sports and media.

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Cortana Analytics Gallery - a scalable community site built on Azure DocumentDB

By Andrew Hoh Program Manager, Azure DocumentDB as written on azure.microsoft.com . Co-authored with Elena Apreutesei, Principal Software Engineer, Azure Machine Learning.

The Cortana Analytics Gallery is a community driven website used to discover, share, and learn about solutions built from the Cortana Analytics Suite. The Gallery hosts a wide range of solutions; everything from a Retail Forecasting experiment to the ever popular Face APIs used in the How old do I look? app. Machine Learning enthusiasts can share their own experiments using the Azure Machine Learning Studio, a private space focused on Machine Learning experimentation and model creation.

The Cortana Analytics Gallery follows a micro service architecture with single purpose components working together to deliver reliable and durable functionality. This post focuses on the Gallery Catalog API, which is used as the data master within the Gallery user experience.

Gallery Catalog API

Every Gallery entity has a JSON metadata document stored in Azure DocumentDB and all CRUD (create, read, update, and delete) operations are against DocumentDB. As a micro service, the Gallery Catalog API provides REST APIs and supports OData; both of which were built through the ASP.NET library WebApi. Generally, the Catalog API pushes the query filters provided through ODATA directly down to the DocumentDB LINQ provider as an ExpressionTree, where it gets executed at the database.

The Gallery Catalog service exposes GET / POST / PATCH / DELETE operations on standard WebAPI routes, such as the generic route /entities/{entityId} and the specialized routes /experiments/{entityId}, /collections/{entityId}, /tutorials/{entityId}, etc.

The JSON objects in the REST API payload are simply the serialized form of the Catalog entity data contracts, derived from a common class EntityBase which provides the flexibility to store other entities.

Source: https://azure.microsoft.com/en-us/blog/cortana-analytics-gallery-a-scalable-community-site-built-on-azure-documentdb/